There are many studies where the analytical task is to estimate the total costs over a defined period of time for a treatment group with a particular condition or chronic disease. These include cost of illness studies such as incremental or total lifetime costs for a disease, the components of cost effectiveness, and other forms of economic evaluation in health care. However, answering such questions requires addressing a range of statistical and econometric issues that include variable time periods of observation for individual patients, fluctuating costs over the course of the disease or treatment, the escalation of costs when the patient is dying and administrative censoring of data prior to the endpoint of interest (e.g. cure, death). These analytical obstacles are compounded by skewed cost data and the endogeneity of treatment decisions caused by self-selection into treatment based on expected idiosyncratic benefits, costs and risks of treatments. Our proposal will develop innovative methods to address each of these problems in a consolidated manner. The proposed work will advance four broad areas in the fields of cost analysis and economic evaluation in health studies. First, it will provide and validate a consistent method of estimating costs in a setting characterized by varying rates of spending over time, right censoring, and the escalation of expenditures commonly observed just before death. Second, it will bridge two large literatures on methods, one on modeling skewed cost data (with right censoring) and the other on the use of IV in the presence of treatment heterogeneity. Third, it can highlight the role that unobserved patient preferences and disease severity may have in generating treatment effect heterogeneity in the context of prostate cancer. Lastly, this work has a high likelihood of generating new information about the comparative cost estimates in prostate cancer which can serve as important inputs into cost-effectiveness and other policy analyses.